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Frequency of rare allelic variation in candidate genes among individuals with low and high urinary calcium excretion - PubMed

  • ️Tue Jan 01 2013

Frequency of rare allelic variation in candidate genes among individuals with low and high urinary calcium excretion

Hakan R Toka et al. PLoS One. 2013.

Abstract

Our study investigated the association of rare allelic variants with extremes of 24-hour urinary calcium excretion because higher urinary calcium excretion is a dominant risk factor for calcium-based kidney stone formation. We resequenced 40 candidate genes potentially related to urinary calcium excretion in individuals from the Nurses' Health Studies I & II and the Health Professionals Follow-up Study. A total of 960 participants were selected based on availability of 24-hour urine collection data and level of urinary calcium excretion (low vs. high). We utilized DNA sample pooling, droplet-based target gene enrichment, multiplexing, and high-throughput sequencing. Approximately 64% of samples (n = 615) showed both successful target enrichment and sequencing data with >20-fold deep coverage. A total of 259 novel allelic variants were identified. None of the rare gene variants (allele frequencies <2%) were found with increased frequency in the low vs. high urinary calcium groups; most of these variants were only observed in single individuals. Unadjusted analysis of variants with allele frequencies ≥ 2% suggested an association of the Claudin14 SNP rs113831133 with lower urinary calcium excretion (6/520 versus 29/710 haplotypes, P value = 0.003). Our data, together with previous human and animal studies, suggest a possible role for Claudin14 in urinary calcium excretion. Genetic validation studies in larger sample sets will be necessary to confirm our findings for rs113831133. In the tested set of candidate genes, rare allelic variants do not appear to contribute significantly to differences in urinary calcium excretion between individuals.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Simplified schematic illustration of the study design utilizing emulsion-based droplet PCR technology and next-generation sequencing.
Figure 2
Figure 2. The flowchart data analysis of identified sequence nucleotide variants (SNVs)

(A). After identifying known SNPs utilizing publically available databases (SNP distribution shown in B), false-positive SNVs were filtered based on frequency in our dataset (present four or more times). The transition to transversion ratio (Ti/Tv) of naturally occurring SNPs supported this analytical approach. dbSNP = Single Nucleotide Polymorphism Database; 1000G = 1000 Genome Project; ESP = Exome Sequencing Project.

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